The present invention relates to networks for managing systems of a building, such as systems which provide heating, ventilation, air conditioning, fire detection, and building access and security; and more particularly to techniques by which the performance of components on the network are monitored.
Large commercial and institutional buildings have several systems for controlling different aspects of the building operation. A heating, ventilation and air conditioning (HVAC) system manages components which control the interior environment of the building. Electrical management systems control the lights and other electrical loads within the building for optimum energy conservation. A security system comprises devices which limit access to the facility to only individuals who possess a proper access code or access device, such as a key card. A fire detection system utilizes heat and smoke detectors located throughout the building to sense the occurrence of a fire and produce a warning of that event.
The components of each of these systems typically are networked together so that the entire building may be controlled from workstations at one or more locations. Such workstations may be located at the manager""s office, the building operating engineer""s office and the security desk. A given building may be part of a larger commercial or educational campus in which case the systems and networks for each building can be connected to a wide area communication network, which enables control from a central campus facility management office.
When a component fails, the system provides a alarm indication of that failure at the workstations. However, it is desirable for the operator to be alerted beforehand of an impending failure. This enables preventative action to be taken. However, the components on the network within a typical building produce so much operational information, it is difficult even for an experienced operator to evaluate the overall performance of the system to detect potential problems. It also is too time consuming to inspect the operating status of every component on the network to pin point ones approaching a malfunction.
This monitoring difficulty is magnified when multiple buildings of a campus are being supervised from a central location.
A general object of the present invention is to provide a technique for monitoring performance of a facility management system and indicating that performance to a human operator.
Another object is to provide a hierarchy of indices which characterize the performance of different levels of the facility management system.
A further object of the present invention is to provide a set of indices which characterize the overall performance of the entire facility management system.
Yet another object is to provide a different set of indices which characterize performance of each subsystem in the facility management system.
A still further object of the present invention is to provide data representing the various operational parameters of the subsystems which enable an operator to pin point functional deficiencies before a catastrophic condition occurs.
These and other objectives are satisfied by a method in which the facilities management system is subdivided into a plurality of subsystems. Data is produced which denotes a plurality of operational parameters for each subsystem. A global performance index for each subsystem is derived from the current values of its operational parameters. From those global performance indices for the subsystems, a universal performance index is derived for entire facilities management system.
In the preferred implementation of this method, the operational parameter data is normalized so that the data for every parameter fall with in the same range of values. The data for each operational parameter also may be averaged separately over a given period of time to minimize the effects that a momentary aberration has on the data. A weighted averaging technique may be employed in which the data occurring at a given point in time is given more importance that data occurring at other times. Preferably the global performance index for each subsystem is derived by performing a weighted averaging on the parameter data. Similarly the universal performance index is derived by averaging the global indices.